Method of Image Denoising Based on Curvelet Transform and Total Variation

ZHOU Zhi-li; WAN Deng-lu

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Method of Image Denoising Based on Curvelet Transform and Total Variation

更新时间：2026-09-04

- Method of Image Denoising Based on Curvelet Transform and Total Variation
- Vol. 30, Issue 12, Pages: 61-63(2013)
- 作者机构：
  
  1. 浙江工贸学院电子系,浙江,温州,325003
  2. 浙江工贸学院电子信息研究院,浙江,温州,325003
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2013
- 稿件说明：
移动端阅览
周志立, 万登泸. 基于曲波变换与整体变分的图像去噪算法[J]. 微电子学与计算机, 2013, 30(12): 61-63,68.

ZHOU Zhi-li, WAN Deng-lu. Method of Image Denoising Based on Curvelet Transform and Total Variation[J]. 2013, 30(12): 61-63.
周志立, 万登泸. 基于曲波变换与整体变分的图像去噪算法[J]. 微电子学与计算机, 2013, 30(12): 61-63,68. DOI：

ZHOU Zhi-li, WAN Deng-lu. Method of Image Denoising Based on Curvelet Transform and Total Variation[J]. 2013, 30(12): 61-63. DOI：

摘要

结合曲波变换与TV两种去噪模型的优点，提出了基于曲波变换与TV模型的去噪方法，用曲波变换的高频系数来检测图像边缘，引入边缘检测函数来引导TV模型的扩散，新模型不仅具有较强的去噪能力，同时图像的边缘信息得到很好的保护。采用峰值信噪比对去噪结果进行客观评价，实验结果表明，新模型的去噪效果明显优于曲波变换阈值法及TV模型。

Abstract

Combining with the advantages of curvelet transform and TV model

proposes a denoising method based on curvelet transform and TV model

which detects the edges of the image with the high-frequency coefficients of curvelet transform

introduces the edge detecting function to guide the TV model diffusion

the new model can not only remove noise

but protect the edges of the image.use peak signal-to-noise ratio to evaluate the denoising results

the experimental results show that the denoising effect of the new model is significantly better than that of the curvelet transform threshold method and TV model.

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